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Python implementation of Krotov's method for quantum optimal control

Project description

Krotov Python Package

Source code on Github Krotov on the Python Package Index Join the chat at https://gitter.im/qucontrol_krotov/Lobby Travis Continuous Integration AppVeyor Continuous Integration Coveralls Documentation Status BSD License

Python implementation of Krotov’s method for quantum optimal control.

This implementation follows the original implementation in the QDYN Fortran library. The method is described in detail in D. M. Reich, M. Ndong, and C. P. Koch, J. Chem. Phys. 136, 104103 (2012) (arXiv:1008.5126)

The krotov package is built on top of QuTiP.

Development happens on Github. You can read the full documentation at ReadTheDocs.

Prerequisites

The Krotov package is available for Python versions >= 3.5. Its main dependency is QuTiP (apart from the core packages of the Python scientific ecosystem). Thus, you should consider QuTiP’s installation instructions.

In any case, using some sort of virtual environment is strongly encouraged. Most packages in the Python scientific ecosystem are now available as wheels, making installation via pip easy. However, QuTiP currently does not provide wheels. Thus, on systems that do not have the necessary compilers installed (Windows, macOS), the conda package manager provides a good solution.

Assuming conda is installed (e.g. through Miniconda), the following commands set up a virtual (conda) environment into which the Krotov package can then be installed:

$ conda create -n qucontrolenv python=3.6
$ conda activate qucontrolenv
$ conda config --append channels conda-forge
$ conda install qutip

Installation

To install the latest released version of krotov into your current (conda) environment, run this command in your terminal:

$ pip install krotov

This is the preferred method to install the krotov package, as it will always install the most recent stable release.

You may also do

$ pip install krotov[dev,extras]

to install additional development dependencies, including packages required to run the example notebooks.

If you don’t have pip installed, this Python installation guide, respectively the Python Packaging User Guide can guide you through the process.

To install the latest development version of krotov from Github:

$ pip install git+https://github.com/qucontrol/krotov.git@master#egg=krotov

Usage

To use Krotov’s method for quantum optimal control in a Python script or Jupyter notebook, start with:

import krotov

Then,

  • define the necessary quantum operators and states using QuTiP.
  • create a list of objectives, as instances of krotov.Objective
  • call krotov.optimize_pulses to perform an optimization of an arbitrary number of control fields over all the objectives.

See Using Krotov with QuTiP and Examples for details.

History

0.1.0 (2018-12-24)

  • Initial release with complete implementatin of first-order Krotov’s method
  • Support for state-to-state and gate optimization, for both closed and open systems

0.0.1 (2018-11-06)

  • Non-functional placeholder release

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